{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "684fb43e",
   "metadata": {},
   "source": [
    "# ONNX Relax 测试"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95361a91",
   "metadata": {},
   "outputs": [],
   "source": [
    "path = \"/media/pc/data/board/arria10/lxw/tasks/tools/npuusertools/models/test/nanotrack_head/nanotrack_head.onnx\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3bdf66bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "import onnx\n",
    "import tvm\n",
    "from tvm import relax\n",
    "from tvm.relax.frontend.onnx import from_onnx\n",
    "model = onnx.load(path)\n",
    "\n",
    "mod = from_onnx(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4b0c7836",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"highlight\" style=\"background: \"><pre style=\"line-height: 125%;\"><span></span><span style=\"color: #007979; font-style: italic\"># from tvm.script import ir as I</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import tir as T</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import relax as R</span>\n",
       "\n",
       "<span style=\"color: #AA22FF\">@I</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>ir_module\n",
       "<span style=\"color: #008000; font-weight: bold\">class</span> <span style=\"color: #0000FF; font-weight: bold\">Module</span>:\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">maximum</span>(A: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_maximum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_maximum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_maximum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_maximum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>max(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">maximum1</span>(A: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_maximum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_maximum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_maximum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_maximum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>max(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">minimum</span>(lv24: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_minimum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_minimum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(lv24[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_minimum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_minimum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>min(lv24[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">minimum1</span>(lv84: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_minimum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_minimum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(lv84[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_minimum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_minimum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>min(lv84[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">main</span>(input1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), input2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        R<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;num_input&quot;</span>: <span style=\"color: #008000\">2</span>})\n",
       "        cls <span style=\"color: #AA22FF; font-weight: bold\">=</span> Module\n",
       "        <span style=\"color: #008000; font-weight: bold\">with</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>dataflow():\n",
       "            lv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>strided_slice(input1, (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">2</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">2</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">6</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">1</span>),), assume_inbound<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">False</span>)\n",
       "            lv1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input1, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">0</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">1</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv3: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">2</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv4: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">3</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv5: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv1, lv2)\n",
       "            lv6: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv5, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>]))\n",
       "            lv7: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>permute_dims(lv6, axes<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">1</span>])\n",
       "            lv8: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv3, lv4)\n",
       "            lv9: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv7, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv10: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv8, lv9, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv11: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>mean(lv10, axis<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">3</span>], keepdims<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "            lv12: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv11, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">4</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv13: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">5</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv14: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv12, lv13)\n",
       "            lv15: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv14)\n",
       "            lv16: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv15, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">6</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv17: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">7</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv18: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv16, lv17)\n",
       "            lv19: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>sigmoid(lv18)\n",
       "            lv20: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>multiply(lv10, lv19)\n",
       "            lv21: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv20, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">8</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">64</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv22: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">9</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv23: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv21, lv22)\n",
       "            lv24 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum, (lv23, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv25 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum, (lv24, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv26: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv25, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">10</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv27: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">11</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv28: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input1, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">12</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv29: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">13</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv30: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">14</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv31: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">15</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv32: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv28, lv29)\n",
       "            lv33: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv32, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>]))\n",
       "            lv34: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>permute_dims(lv33, axes<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">1</span>])\n",
       "            lv35: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv30, lv31)\n",
       "            lv36: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv34, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv37: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv35, lv36, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv38: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>mean(lv37, axis<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">3</span>], keepdims<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "            lv39: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv38, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">16</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv40: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">17</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv41: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv39, lv40)\n",
       "            lv42: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv41)\n",
       "            lv43: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv42, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">18</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv44: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">19</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv45: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv43, lv44)\n",
       "            lv46: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>sigmoid(lv45)\n",
       "            lv47: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>multiply(lv37, lv46)\n",
       "            lv48: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv47, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">20</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">64</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv49: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">21</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv50: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv48, lv49)\n",
       "            lv51 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum, (lv50, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv52 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum, (lv51, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv53: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv52, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">22</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv54: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">23</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv55: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>strided_slice(lv, (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">3</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">2</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">6</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">1</span>),), assume_inbound<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">False</span>)\n",
       "            lv56: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv55, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">24</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv57: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">25</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv58: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">26</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv59: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">27</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv60: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv56, lv57)\n",
       "            lv61: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv58, lv59)\n",
       "            lv62: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv60, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>]))\n",
       "            lv63: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv55, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">28</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv64: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">29</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv65: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">30</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv66: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">31</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv67: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv63, lv64)\n",
       "            lv68: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv65, lv66)\n",
       "            lv69: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv67, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>]))\n",
       "            lv70: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv26, lv27)\n",
       "            lv71: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv61, lv62, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv72: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">160</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>concat((lv70, lv71), axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>)\n",
       "            lv73: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv72, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">32</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv74: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">33</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv75: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv53, lv54)\n",
       "            lv76: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv68, lv69, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv77: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">160</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>concat((lv75, lv76), axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>)\n",
       "            lv78: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv77, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">34</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv79: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">35</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv80: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv78, lv79)\n",
       "            lv81: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv80, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">36</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv82: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">37</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv83: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv81, lv82)\n",
       "            lv84 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv83, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv85 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv84, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv86: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv85, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">38</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv87: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">39</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv88: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv86, lv87)\n",
       "            lv89: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv88, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">40</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv90: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">41</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv91: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv89, lv90)\n",
       "            lv92 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv91, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv93 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv92, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv94: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv93, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">42</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv95: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">43</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv96: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv94, lv95)\n",
       "            lv97: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv96, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">44</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv98: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">45</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv99: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv97, lv98)\n",
       "            lv100 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv99, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv101 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv100, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv102: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv101, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">46</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv103: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">47</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv104: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv102, lv103)\n",
       "            lv105: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv104, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">48</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv106: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">49</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv107: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv105, lv106)\n",
       "            lv108 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv107, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv109 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv108, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv110: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv109, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">50</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv111: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">51</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv112: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv110, lv111)\n",
       "            lv113: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv112, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">52</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv114: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">53</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv115: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv113, lv114)\n",
       "            lv116 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv115, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv117 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv116, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv118: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv117, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">54</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv119: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">55</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv120: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv118, lv119)\n",
       "            lv121: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv120, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">56</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv122: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">57</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv123: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv121, lv122)\n",
       "            lv124 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv123, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv125 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv124, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv126: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv125, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">58</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv127: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">59</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv128: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv126, lv127)\n",
       "            lv129: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv128, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">60</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv130: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">61</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv131: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv73, lv74)\n",
       "            lv132: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv131, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">62</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv133: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">63</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv134: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv132, lv133)\n",
       "            lv135 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv134, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv136 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv135, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv137: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv136, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">64</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv138: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">65</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv139: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv137, lv138)\n",
       "            lv140: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv139, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">66</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv141: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">67</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv142: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv140, lv141)\n",
       "            lv143 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv142, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv144 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv143, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv145: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv144, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">68</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv146: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">69</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv147: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv145, lv146)\n",
       "            lv148: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv147, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">70</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv149: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">71</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv150: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv148, lv149)\n",
       "            lv151 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv150, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv152 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv151, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv153: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv152, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">72</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv154: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">73</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv155: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv153, lv154)\n",
       "            lv156: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv155, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">74</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv157: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">75</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv158: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv156, lv157)\n",
       "            lv159 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv158, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv160 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv159, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv161: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv160, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">76</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv162: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">77</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv163: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv161, lv162)\n",
       "            lv164: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv163, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">78</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv165: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">79</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv166: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv164, lv165)\n",
       "            lv167 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv166, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv168 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv167, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv169: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv168, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">80</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv170: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">81</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv171: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv169, lv170)\n",
       "            lv172: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv171, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">82</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv173: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">83</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv174: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv172, lv173)\n",
       "            lv175 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv174, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv176 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv175, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv177: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv176, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">84</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv178: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">85</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv179: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv177, lv178)\n",
       "            lv180: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv179, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">86</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv181: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">87</span>], R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv182: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv180, lv181)\n",
       "            lv183: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv129, lv130)\n",
       "            lv184: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>exp(lv182)\n",
       "            gv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv183, lv184\n",
       "            R<span style=\"color: #AA22FF; font-weight: bold\">.</span>output(gv)\n",
       "        <span style=\"color: #008000; font-weight: bold\">return</span> gv\n",
       "\n",
       "<span style=\"color: #007979; font-style: italic\"># Metadata omitted. Use show_meta=True in script() method to show it.</span>\n",
       "</pre></div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mod.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "abba85d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "fold_pipeline = tvm.transform.Sequential([\n",
    "    relax.transform.FoldBatchnormToConv2D(),\n",
    "    relax.transform.FoldConstant(),\n",
    "    relax.transform.RemoveRedundantReshape(),\n",
    "    # 将 BatchNorm 转换为一组更简单的算子以进行融合\n",
    "    relax.transform.DecomposeOpsForInference(),\n",
    "    # 规范化绑定\n",
    "    relax.transform.CanonicalizeBindings(),\n",
    "\n",
    "])\n",
    "# 初次优化模型\n",
    "run_mod = fold_pipeline(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f137fa54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"highlight\" style=\"background: \"><pre style=\"line-height: 125%;\"><span></span><span style=\"color: #007979; font-style: italic\"># from tvm.script import ir as I</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import tir as T</span>\n",
       "<span style=\"color: #007979; font-style: italic\"># from tvm.script import relax as R</span>\n",
       "\n",
       "<span style=\"color: #AA22FF\">@I</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>ir_module\n",
       "<span style=\"color: #008000; font-weight: bold\">class</span> <span style=\"color: #0000FF; font-weight: bold\">Module</span>:\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">maximum</span>(A: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_maximum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_maximum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_maximum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_maximum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>max(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">maximum1</span>(A: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_maximum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_maximum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_maximum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_maximum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>max(A[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">minimum</span>(lv24: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_minimum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">64</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_minimum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(lv24[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_minimum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_minimum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>min(lv24[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@T</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_func(private<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">minimum1</span>(lv84: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), B: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((), <span style=\"color: #BA2121\">&quot;float32&quot;</span>), T_minimum: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>Buffer((T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)), <span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        T<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;tir.noalias&quot;</span>: T<span style=\"color: #AA22FF; font-weight: bold\">.</span>bool(<span style=\"color: #008000; font-weight: bold\">True</span>)})\n",
       "        <span style=\"color: #007979; font-style: italic\"># with T.block(&quot;root&quot;):</span>\n",
       "        <span style=\"color: #008000; font-weight: bold\">for</span> ax0, ax1, ax2, ax3 <span style=\"color: #008000; font-weight: bold\">in</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>grid(T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">1</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">96</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>), T<span style=\"color: #AA22FF; font-weight: bold\">.</span>int64(<span style=\"color: #008000\">15</span>)):\n",
       "            <span style=\"color: #008000; font-weight: bold\">with</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>block(<span style=\"color: #BA2121\">&quot;T_minimum&quot;</span>):\n",
       "                v_ax0, v_ax1, v_ax2, v_ax3 <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>axis<span style=\"color: #AA22FF; font-weight: bold\">.</span>remap(<span style=\"color: #BA2121\">&quot;SSSS&quot;</span>, [ax0, ax1, ax2, ax3])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>reads(lv84[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "                T<span style=\"color: #AA22FF; font-weight: bold\">.</span>writes(T_minimum[v_ax0, v_ax1, v_ax2, v_ax3])\n",
       "                T_minimum[v_ax0, v_ax1, v_ax2, v_ax3] <span style=\"color: #AA22FF; font-weight: bold\">=</span> T<span style=\"color: #AA22FF; font-weight: bold\">.</span>min(lv84[v_ax0, v_ax1, v_ax2, v_ax3], B[()])\n",
       "\n",
       "    <span style=\"color: #AA22FF\">@R</span><span style=\"color: #AA22FF; font-weight: bold\">.</span>function\n",
       "    <span style=\"color: #008000; font-weight: bold\">def</span> <span style=\"color: #0000FF\">main</span>(input1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), input2: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">-&gt;</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)):\n",
       "        R<span style=\"color: #AA22FF; font-weight: bold\">.</span>func_attr({<span style=\"color: #BA2121\">&quot;num_input&quot;</span>: <span style=\"color: #008000\">2</span>})\n",
       "        cls <span style=\"color: #AA22FF; font-weight: bold\">=</span> Module\n",
       "        <span style=\"color: #008000; font-weight: bold\">with</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>dataflow():\n",
       "            lv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>strided_slice(input1, (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">2</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">2</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">6</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">1</span>),), assume_inbound<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">False</span>)\n",
       "            lv1: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input1, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">0</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv3: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">1</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv5: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv1, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">2</span>])\n",
       "            lv6: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv5, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>]))\n",
       "            lv7: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>permute_dims(lv6, axes<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">1</span>])\n",
       "            lv8: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv3, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">3</span>])\n",
       "            lv9: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv7, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv10: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv8, lv9, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv11: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>mean(lv10, axis<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">3</span>], keepdims<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "            lv12: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv11, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">4</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv14: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv12, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">5</span>])\n",
       "            lv15: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv14)\n",
       "            lv16: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv15, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">6</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv18: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv16, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">7</span>])\n",
       "            lv19: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>sigmoid(lv18)\n",
       "            lv20: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>multiply(lv10, lv19)\n",
       "            lv21: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv20, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">8</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">64</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv23: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv21, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">9</span>])\n",
       "            lv24 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum, (lv23, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv25 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum, (lv24, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv26: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv25, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">10</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv28: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input1, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">11</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv30: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">12</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv32: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">8</span>, <span style=\"color: #008000\">8</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv28, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">13</span>])\n",
       "            lv33: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv32, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">64</span>]))\n",
       "            lv34: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>permute_dims(lv33, axes<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">1</span>])\n",
       "            lv35: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv30, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">14</span>])\n",
       "            lv36: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv34, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>]))\n",
       "            lv37: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv35, lv36, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv38: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>mean(lv37, axis<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">3</span>], keepdims<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">True</span>)\n",
       "            lv39: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv38, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">15</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv41: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv39, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">16</span>])\n",
       "            lv42: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>relu(lv41)\n",
       "            lv43: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv42, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">17</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv45: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv43, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">18</span>])\n",
       "            lv46: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>sigmoid(lv45)\n",
       "            lv47: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>multiply(lv37, lv46)\n",
       "            lv48: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv47, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">19</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">64</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv50: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv48, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">20</span>])\n",
       "            lv51 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum, (lv50, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv52 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum, (lv51, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv53: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv52, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">21</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv55: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>strided_slice(lv, (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">3</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">2</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">6</span>),), (R<span style=\"color: #AA22FF; font-weight: bold\">.</span>prim_value(<span style=\"color: #008000\">1</span>),), assume_inbound<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000; font-weight: bold\">False</span>)\n",
       "            lv56: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv55, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">22</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv58: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">23</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv60: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv56, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">24</span>])\n",
       "            lv61: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv58, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">25</span>])\n",
       "            lv62: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv60, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>]))\n",
       "            lv63: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv55, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">26</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv65: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(input2, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">27</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv67: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv63, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">28</span>])\n",
       "            lv68: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">16</span>, <span style=\"color: #008000\">16</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv65, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">29</span>])\n",
       "            lv69: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>reshape(lv67, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>shape([<span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">4</span>]))\n",
       "            lv70: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv26, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">30</span>])\n",
       "            lv71: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv61, lv62, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv72: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">160</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>concat((lv70, lv71), axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>)\n",
       "            lv73: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv72, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">31</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv75: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">64</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv53, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">32</span>])\n",
       "            lv76: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv68, lv69, strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv77: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">160</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>concat((lv75, lv76), axis<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>)\n",
       "            lv78: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv77, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">33</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv80: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv78, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">34</span>])\n",
       "            lv81: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv80, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">35</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv83: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv81, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">36</span>])\n",
       "            lv84 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv83, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv85 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv84, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv86: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv85, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">37</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv88: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv86, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">38</span>])\n",
       "            lv89: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv88, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">39</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv91: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv89, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">40</span>])\n",
       "            lv92 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv91, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv93 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv92, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv94: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv93, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">41</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv96: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv94, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">42</span>])\n",
       "            lv97: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv96, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">43</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv99: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv97, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">44</span>])\n",
       "            lv100 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv99, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv101 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv100, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv102: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv101, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">45</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv104: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv102, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">46</span>])\n",
       "            lv105: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv104, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">47</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv107: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv105, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">48</span>])\n",
       "            lv108 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv107, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv109 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv108, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv110: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv109, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">49</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv112: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv110, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">50</span>])\n",
       "            lv113: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv112, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">51</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv115: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv113, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">52</span>])\n",
       "            lv116 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv115, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv117 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv116, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv118: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv117, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">53</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv120: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv118, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">54</span>])\n",
       "            lv121: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv120, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">55</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv123: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv121, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">56</span>])\n",
       "            lv124 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv123, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv125 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv124, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv126: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv125, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">57</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv128: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv126, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">58</span>])\n",
       "            lv129: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv128, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">59</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv131: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv73, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">60</span>])\n",
       "            lv132: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv131, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">61</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv134: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv132, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">62</span>])\n",
       "            lv135 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv134, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv136 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv135, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv137: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv136, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">63</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv139: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv137, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">64</span>])\n",
       "            lv140: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv139, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">65</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv142: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv140, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">66</span>])\n",
       "            lv143 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv142, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv144 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv143, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv145: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv144, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">67</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv147: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv145, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">68</span>])\n",
       "            lv148: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv147, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">69</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv150: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv148, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">70</span>])\n",
       "            lv151 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv150, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv152 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv151, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv153: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv152, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">71</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv155: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv153, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">72</span>])\n",
       "            lv156: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv155, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">73</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv158: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv156, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">74</span>])\n",
       "            lv159 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv158, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv160 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv159, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv161: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv160, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">75</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv163: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv161, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">76</span>])\n",
       "            lv164: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv163, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">77</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv166: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv164, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">78</span>])\n",
       "            lv167 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv166, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv168 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv167, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv169: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv168, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">79</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv171: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv169, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">80</span>])\n",
       "            lv172: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv171, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">81</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">96</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv174: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv172, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">82</span>])\n",
       "            lv175 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>maximum1, (lv174, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">0.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv176 <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>call_tir(cls<span style=\"color: #AA22FF; font-weight: bold\">.</span>minimum1, (lv175, R<span style=\"color: #AA22FF; font-weight: bold\">.</span>const(<span style=\"color: #008000\">6.0</span>, <span style=\"color: #BA2121\">&quot;float32&quot;</span>)), out_sinfo<span style=\"color: #AA22FF; font-weight: bold\">=</span>R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>))\n",
       "            lv177: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv176, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">83</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv179: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">96</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv177, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">84</span>])\n",
       "            lv180: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>nn<span style=\"color: #AA22FF; font-weight: bold\">.</span>conv2d(lv179, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">85</span>], strides<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], padding<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>, <span style=\"color: #008000\">0</span>], dilation<span style=\"color: #AA22FF; font-weight: bold\">=</span>[<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">1</span>], groups<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #008000\">1</span>, data_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, kernel_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;OIHW&quot;</span>, out_layout<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;NCHW&quot;</span>, out_dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;void&quot;</span>)\n",
       "            lv182: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv180, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">86</span>])\n",
       "            lv183: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>add(lv129, metadata[<span style=\"color: #BA2121\">&quot;relax.expr.Constant&quot;</span>][<span style=\"color: #008000\">87</span>])\n",
       "            lv184: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>) <span style=\"color: #AA22FF; font-weight: bold\">=</span> R<span style=\"color: #AA22FF; font-weight: bold\">.</span>exp(lv182)\n",
       "            gv: R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tuple(R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">2</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>), R<span style=\"color: #AA22FF; font-weight: bold\">.</span>Tensor((<span style=\"color: #008000\">1</span>, <span style=\"color: #008000\">4</span>, <span style=\"color: #008000\">15</span>, <span style=\"color: #008000\">15</span>), dtype<span style=\"color: #AA22FF; font-weight: bold\">=</span><span style=\"color: #BA2121\">&quot;float32&quot;</span>)) <span style=\"color: #AA22FF; font-weight: bold\">=</span> lv183, lv184\n",
       "            R<span style=\"color: #AA22FF; font-weight: bold\">.</span>output(gv)\n",
       "        <span style=\"color: #008000; font-weight: bold\">return</span> gv\n",
       "\n",
       "<span style=\"color: #007979; font-style: italic\"># Metadata omitted. Use show_meta=True in script() method to show it.</span>\n",
       "</pre></div>\n"
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